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  • J Electr Eng Technol.2015; 10(?): 30-40 http://dx.doi.org/10.5370/JEET.2015.10.2.030

    30

    Copyright The Korean Institute of Electrical Engineers This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/

    licenses/by-nc/3.0/)which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

    Design and Implementation of Direct Torque Control Based on an Intelligent Technique of Induction Motor on FPGA

    Saber Krim, Soufien Gdaim*, Abdellatif Mtibaa** and Mohamed Faouzi Mimouni***

    Abstract In this paper the hardware implementation of the direct torque control based on the fuzzy logic technique of induction motor on the Field-Programmable Gate Array (FPGA) is presented. Due to its complexity, the fuzzy logic technique implemented on a digital system like the DSP (Digital Signal Processor) and microcontroller is characterized by a calculating delay. This delay is due to the processing speed which depends on the system complexity. The limitation of these solutions is inevitable. To solve this problem, an alternative digital solution is used, based on the FPGA, which is characterized by a fast processing speed, to take the advantage of the performances of the fuzzy logic technique in spite of its complex computation. The Conventional Direct Torque Control (CDTC) of the induction machine faces problems, like the high stator flux, electromagnetic torque ripples, and stator current distortions. To overcome the CDTC problems many methods are used such as the space vector modulation which is sensitive to the parameters variations of the machine, the increase in the switches inverter number which increases the cost of the inverter, and the artificial intelligence. In this paper an intelligent technique based on the fuzzy logic is used because it is allows controlling the systems without knowing the mathematical model. Also, we use a new method based on the Xilinx system generator for the hardware implementation of Direct Torque Fuzzy Control (DTFC) on the FPGA. The simulation results of the DTFC are compared to those of the CDTC. The comparison results illustrate the reduction in the torque and stator flux ripples of the DTFC and show the Xilinx Virtex V FPGA performances in terms of execution time.

    Keywords: Direct torque control, Fuzzy Logic Control (FLC), Induction motor, Real time, Xilinx system generator, FPGA.

    1. Introduction In the last few years, the most digital implementations of

    control algorithms of electric machines are based on software solutions such as microcontrollers and digital signal processor. However, these solutions present some disadvantages; for example, the used sampling period is limited by the time of computation. To overcome the traditional software solution limitations, new hardware solutions such as the FPGAs can be used, which present the appropriate digital solutions for the implementation of control algorithms. The inherent parallelism of these new digital solutions as well as their large computing capacity, making computation time delays, are negligible despite the complexity of the algorithms to implement.

    The conventional direct torque control of the induction motor is characterized by outstanding dynamic performances

    as well as good robustness to against changes of motor parameters. However, the Conventional Direct Torque Control (CDTC) also has some drawbacks, like high electromagnetic torque and stator flux ripples and high stator current distortion [1-3]. To improve the CDTC performances, many methods are used, such as the fuzzy logic control, the Space Vector Modulation (SVM) [4-6], and the increase in the switches inverter number [7]. Nevertheless, the use of SVM needs several motor parameters and increases the complexity of the Direct Torque Control (DTC) algorithm. Moreover, the rise in the switches inverter number increases costs. In this work, our orientation is focused to the fuzzy logic control, because it is an effective technique used where mathematical model is complicated or the mathematical model does not exist, as well it is allows controlling the systems without knowing the mathematical model. The objective of this work is to implement the Direct Torque Fuzzy Control (DTFC) of the induction motor on the FPGA in order to take advantage of these performances in the field of digital control of electrical machines in real time. The Fuzzy Logic Control (FLC) is used to replace the switching table, the sector block and the two hysteresis comparators [8].

    During the last few years several researchers use the hardware implementation on the FPGA for controlling

    Corresponding Author: Laboratory of Electronics and Micro-electronics of the FSM, University of Monastir, Tunisia. (krimsaber @hotmail.fr).

    * Laboratory of Electronics and Microelectronics of the FSM, University of Monastir, Tunisia. ({sgdaim, abdellatif.mtibaa}@enim. rnu.tn)

    ** Research Unit of industrial systems Study and renewable energy (ESIER), National Engineering School, University of Monastir, Tunisia. (Mfaouzi.mimouni@enim.rnu.tn).

    Received : October 17, 2014; Accepted : December 27, 2014

    ISSN(Print) 1975-0102ISSN(Online) 2093-7423

  • Saber Krim, Soufien Gdaim, Abdellatif Mtibaa and Mohamed Faouzi Mimouni

    http://www.jeet.or.kr 31

    electrical system [9-15]. Most of them use the VHDL (VHSIC hardware description language). In this study, the Xilinx System Generator (XSG) is used to automatically generate the VHDL code. The advantages of this method are the rapid time to market, real time, and portability.

    2. Contributions of Xilinx System Generator

    The XSG is a modeling tool developed by the Xilinx to

    design implemented systems on the FPGA. It has a library of varied blocks, which can be automatically compiled into an FPGA [16]. In this work, the (XSG) is used to implement the DTFC architecture of the induction motor based on Fuzzy Logic Control (FLC) algorithm on an FPGA. In the first step, we begin by implementing the proposed architectures using the XSG blocks available on the Simulink library. Once the Design of the system is completed and gives the desired simulation results, the VHDL code can be generated by the XSG tool [17]. The design flow of the XSG is given in Fig. 1. After generating the VHDL code and the synthesis, we can generate the bitstream file. Then we can move this configuration file to program the FPGA [18].

    Fig. 1. Xilinx system generator design flow

    3. Basic CDTC Principle of Induction Motor

    3.1 Induction machine model

    The model of the induction motor expressed in the

    stationary axes reference frame can be described by [19]:

    S r

    S S r rS SS

    r S

    R Rdi L L R

    idt L Li

    += +

    1

    1

    S SS S

    S r

    S S rS S S

    S

    rS S

    r S S

    SS S S

    SS S S

    vL L

    R Rdi L L

    i idt L

    Rv

    L L Ld

    R idt

    dR i v

    dt

    v

    + +

    += +

    + +

    = +

    = +

    (1)

    where, iS, S, VS, R, and L denote the stator currents, stator flux, stator voltage, resistance, and inductance, respectively,

    and where denotes the rotor speed and 2

    1 ms r

    LL L

    = is

    the redefined leakage inductance. The electromagnetic torque of the induction motor can

    be expressed in terms of stator currents and stator flux, which is given by the following expression:

    _3 ( )2em est s s s s

    T p i i = (2)

    The mechanical speed equation is given by the following

    equation:

    3 ( )2

    Ls s s s

    Td p i i fdt J

    = (3)

    where p is the number of pole pairs, J and TL denote the moment of inertia of the motor and the load torque, is the rotor mechanical speed (p=), and f is a viscous friction coefficient.

    3.2 CDTC Principle

    The basic principle of the CDTC is based on the

    application of a voltage particular sequence via a voltage inverter, whose waves are generated through hysteresis comparators in which the flux and torque are trapped to follow their references [20]. The components of the stator voltage vector in the stationary reference frame are calculated as follows:

    2 ( )3 21 ( )2

    b bs dc a

    s dc b c

    S Sv v S

    v v S S

    +=

    =

    (4)

    where Vdc is the DC bus voltage.

    The components of the stator current vector are given by the following expression:

  • Design and Implementation of Direct Torque Control Based on an Intelligent Technique of Induction Motor on FPGA

    32 J Electr Eng Technol.2015;10(1): 30-40

    32

    1 ( )2

    s sa

    s sb sc

    i i

    i i i

    =

    =

    (5)

    The module of the stator flux is given by Eq. 6:

    2 2s s s = + (6)

    The angle between the stator flux ( , )s s s and the

    reference axis is given by Eq. (7):

    ( )sss

    arctg

    = (7)

    The estimated values of the torque and stator flux are

    compared to the reference values Te* and S*, respectively. It can be seen from Fig. 3 that the error between the estimated torque Te and the reference torque Te* is the input of a three level hysteresis comparator, where the error between the estimated stator flux magnitude S and the reference stator flux magnitude S* is the input of a two level hysteresis comparator.

    Finally, the outputs of the comparators with a stator flux sector, where the stator flux space vector is located, select an appropriate inverter voltage vector from the switching table (Table 1). The selected voltage vector will be